Directory Contents

Directory Contents#

Listing files and directories with os.listdir

by Silvia Mazzoni, DesignSafe, 2025

Once you’ve confirmed that a path exists, you can explore its contents using Python.
The simplest way to do this is with os.listdir, which returns a list of all files and folders inside the specified directory.

File handling in Python lives in two main places:

os/os.path: low-level, battle‑tested utilities (list directories, join paths, check existence).
pathlib: a modern, object‑oriented layer that makes paths feel like first‑class objects (with methods for globbing, reading, writing, etc.).

When you need wildcards like *.out or *Lcol12.out, don’t shell out to ls. Instead, use Python’s built‑ins (glob or pathlib.Path.glob) so your code is portable, safe, and testable.

import os

# Test Path:
myPath = '~/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp'
dataDir =os.path.abspath(os.path.expanduser(myPath))

print('thisPath:',dataDir)
print('exists:',os.path.exists(dataDir))

thisPath: /home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp
exists: True

os.listdir(): Simple Directory Listing#

os.listdir(path) returns all entries (files and subdirectories) in a directory—no filtering by pattern:

entries = os.listdir(dataDir)          # Just names, not full paths
entries_full = [os.path.join(dataDir, e) for e in entries]

for i in range(min(10,len(entries_full))):
    print(entries_full[i])

/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol141.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol149.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol139.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol144.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol143.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol142.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol209.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol148.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol138.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol145.0.out

Key points

Returns everything in the directory (files + subdirs).
No pattern matching—you must filter yourself:

Lcol = 100.0

matches = [f for f in entries if f.endswith(f"Lcol{Lcol}.out")]

for i in range(min(10,len(matches))):
    print(matches[i])

DBase_Lcol100.0.out
DCol_Lcol100.0.out
DFree_Lcol100.0.out
FCol_Lcol100.0.out
RBase_Lcol100.0.out

Names are returned without the directory prefix; prepend dataDir if you need full paths.
Order is not guaranteed; sort if you care about stable output:

entries = sorted(os.listdir(dataDir))

for i in range(min(10,len(entries))):
    print(entries[i])

DBase_Lcol10.0.out
DBase_Lcol100.0.out
DBase_Lcol1000.0.out
DBase_Lcol1001.0.out
DBase_Lcol1002.0.out
DBase_Lcol1003.0.out
DBase_Lcol1004.0.out
DBase_Lcol1005.0.out
DBase_Lcol1006.0.out
DBase_Lcol1007.0.out

Use os.listdir() when you want a quick, unconditional list of contents and you’ll handle filtering in Python.

Wildcards the Right Way: glob and pathlib#

Unlike os.listdir(), which returns all files in a directory without filtering, the glob module lets you use wildcard patterns (***, ?, [ranges]) to match specific filenames — similar to how you would in a shell command like *ls .txt.

glob.glob()#

import glob, os

pattern = os.path.join(dataDir, f"*Lcol{Lcol}.out")
files = sorted(glob.glob(pattern))      # sort for predictable order
for f in files:
    print(f)

/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DCol_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DFree_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/FCol_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/RBase_Lcol100.0.out

pathlib.Path.glob()#

from pathlib import Path

files = sorted(Path(dataDir).glob(f"*Lcol{Lcol}.out"))
for p in files:
    print(p)                            # Path objects; str(p) if you need strings

/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DCol_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DFree_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/FCol_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/RBase_Lcol100.0.out

Recursive matching (subdirectories too) uses **:

from pathlib import Path

icnt = 0
for p in Path(dataDir).rglob("*.out"):  # or Path(dataDir).glob("**/*.out")
    print(p)
    icnt += 1
    if icnt>10:
        break

/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol141.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol149.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol139.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol144.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol143.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol142.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol209.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol148.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol138.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol145.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol151.0.out

Why not os.system(‘ls …’)?#

While this works on Unix‑like systems:

os.system(f'ls {dataDir}/*Lcol{Lcol}.out')

/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DCol_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DFree_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/FCol_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/RBase_Lcol100.0.out

…it’s usually a bad trade‑off:

Not cross‑platform: ls doesn’t exist on Windows (without extra tooling).
Brittle: spaces or special characters in paths can break the shell command.
Security risk: string interpolation into a shell command can open injection vulnerabilities.
No return values: you get printed text, not a list you can manipulate in Python.
Harder to test & maintain.

Prefer:

glob.glob() / pathlib.Path.glob() for patterns.
os.listdir() + Python filtering for simple rules.

Why use glob instead of os.system(‘ls …’)?#

Cross-platform — works on Windows, macOS, and Linux
No shell dependency — safer, avoids shell injection risks
Python-native — returns a list of matching filenames for direct processing

Quick Comparison#

Task / Feature	`os.listdir()`	`glob.glob()`	`pathlib.Path.glob()`
List directory contents	✅ (all entries)	✅ (only matches)	✅ (only matches)
Wildcards (`*`, `?`, `[]`)	❌	✅	✅
Recursive search	❌	✅ with `**` + `recursive=True`	✅ via `rglob()` or `glob("**/pattern")`
Returns	Names (no dir)	Matching paths (strings)	Matching paths (`Path` objects)
Path operations (join, parent, stem)	Manual with `os.path`	Manual with `os.path`	Built-in via `Path` methods
Cross‑platform & safe	✅	✅	✅
Sorted results guaranteed	❌ (use `sorted(...)`)	❌ (wrap with `sorted(...)`)	❌ (wrap with `sorted(...)`)

Example of recursive glob (stdlib style):

import glob, os
pattern = os.path.join(dataDir, "**", "*.out")
files = sorted(glob.glob(pattern, recursive=True))
for f in files[0:min(10,len(files))]:
    print(f)             # line-by-line like `ls`

/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol10.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol1000.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol1001.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol1002.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol1003.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol1004.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol1005.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol1006.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol1007.0.out

Drop‑in Replacement for `ls {dataDir}/*Lcol{Lcol}.out`#

import glob, os

pattern = os.path.join(dataDir, f"*Lcol{Lcol}.out")
files = sorted(glob.glob(pattern))
for f in files[0:min(10,len(files))]:
    print(f)             # line-by-line like `ls`
print('')
# or:
print(" ".join(files))   # single line, space-separated

/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DCol_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DFree_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/FCol_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/RBase_Lcol100.0.out

/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol100.0.out /home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DCol_Lcol100.0.out /home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DFree_Lcol100.0.out /home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/FCol_Lcol100.0.out /home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/RBase_Lcol100.0.out

Pathlib version

from pathlib import Path

files = sorted(Path(dataDir).glob(f"*Lcol{Lcol}.out"))

for p in files[0:min(10,len(files))]:
    print(p)

/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DCol_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DFree_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/FCol_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/RBase_Lcol100.0.out

Best Practices & Gotchas#

Always sort if order matters:

files = sorted(files)

for p in files[0:min(10,len(files))]:
    print(p)

/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DBase_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DCol_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/DFree_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/FCol_Lcol100.0.out
/home/jupyter/MyData/tapis-jobs-archive/2025-08-14Z/1739a4ea-bc83-419b-9a6d-7823b81c797c-007/inputDirectory/DataTCLmp/RBase_Lcol100.0.out

Prefer pathlib in new code; it reads cleaner and reduces os.path boilerplate.
Be explicit about recursion: rglob("*.ext") or glob("**/*.ext", recursive=True).
Avoid shelling out for path tasks—keep logic in Python for portability, safety, and easier testing.
Windows notes: paths are handled correctly by os.path/pathlib; wildcard matching is done by Python, not the shell, so behavior is consistent across OSes.

Splitting into files and directories#

To organize this output more clearly, you can separate files and directories using list comprehensions and os.path.isdir:

AllContents = os.listdir(dataDir)

directories = [name for name in AllContents if os.path.isdir(os.path.join(dataDir, name))]

print(f" -- directories:",directories[:20]); # show only the first few

 -- directories: []

files = [name for name in AllContents if not os.path.isdir(os.path.join(dataDir, name))] # select files as not directories

print(f" -- files:",files[:20]); # show only the first few

 -- files: ['DBase_Lcol141.0.out', 'DBase_Lcol149.0.out', 'DBase_Lcol139.0.out', 'DBase_Lcol144.0.out', 'DBase_Lcol143.0.out', 'DBase_Lcol142.0.out', 'DBase_Lcol209.0.out', 'DBase_Lcol148.0.out', 'DBase_Lcol138.0.out', 'DBase_Lcol145.0.out', 'DBase_Lcol151.0.out', 'DBase_Lcol140.0.out', 'DBase_Lcol14.0.out', 'DBase_Lcol15.0.out', 'DBase_Lcol146.0.out', 'DBase_Lcol147.0.out', 'DBase_Lcol195.0.out', 'DBase_Lcol150.0.out', 'DBase_Lcol208.0.out', 'DBase_Lcol137.0.out']

Why this is helpful#

You get a quick overview of what’s inside your data folder.
Separating files vs. directories is especially useful if your scripts process only data files, or need to recursively explore subfolders.
The list of files is stored in an array so you can use it in your workflow

Recipe Box: Common File Listing Patterns#

These short examples cover frequent file-listing tasks using glob, pathlib, and os.

1. List Only Files (no directories)#

import os
files_only = [f for f in os.listdir(dataDir) 
              if os.path.isfile(os.path.join(dataDir, f))]

Pathlib version:

from pathlib import Path
files_only = [p for p in Path(dataDir).iterdir() if p.is_file()]

2. List Only Directories#

dirs_only = [d for d in os.listdir(dataDir) 
             if os.path.isdir(os.path.join(dataDir, d))]

Pathlib version:

dirs_only = [p for p in Path(dataDir).iterdir() if p.is_dir()]

3. Match by Suffix / Extension#

import glob, os
txt_files = glob.glob(os.path.join(dataDir, "*.txt"))

Pathlib version:

txt_files = list(Path(dataDir).glob("*.txt"))

4. Match by Prefix#

prefixed = [f for f in os.listdir(dataDir) if f.startswith("run_")]

5. Recursive Search (all subfolders)#

import glob, os
pattern = os.path.join(dataDir, "**", "*.out")
files = glob.glob(pattern, recursive=True)

Pathlib version:

files = list(Path(dataDir).rglob("*.out"))

6. Natural Sort (sort by embedded numbers, like `file2`, `file10`)#

import re

def natural_key(s):
    return [int(text) if text.isdigit() else text.lower()
            for text in re.split(r'(\d+)', str(s))]

files = sorted(Path(dataDir).glob("*.out"), key=natural_key)

7. Combine Multiple Patterns#

from itertools import chain
import glob, os

patterns = ["*.tcl", "*.py"]
matches = list(chain.from_iterable(
    glob.glob(os.path.join(dataDir, pat)) for pat in patterns
))

Pathlib version:

matches = []
for pat in ["*.tcl", "*.py"]:
    matches.extend(Path(dataDir).glob(pat))

8. Ignore Certain Files#

files = [f for f in os.listdir(dataDir)
         if not f.endswith(".bak") and not f.startswith("temp")]

9. Get Full Paths for All Matches#

full_paths = [os.path.join(dataDir, f) for f in os.listdir(dataDir)]

Pathlib version:

full_paths = list(Path(dataDir).iterdir())

10. Mixed Example: List `.out` files containing `Lcol12`, sorted#

import glob, os
pattern = os.path.join(dataDir, "*Lcol12*.out")
files = sorted(glob.glob(pattern))
for f in files:
    print(f)

Python Paths & Wildcards — Quick Reference Cheat Sheet#

here’s a one-page visual cheat sheet laid out like a quick-reference poster so you can instantly compare os, glob, and pathlib patterns for the same task.

Task	`os` module	`glob` module	`pathlib` module
List all entries in a directory	`os.listdir(path)`	—	`Path(path).iterdir()`
List only files	`[f for f in os.listdir(path) if os.path.isfile(os.path.join(path,f))]`	—	`[p for p in Path(path).iterdir() if p.is_file()]`
List only directories	`[d for d in os.listdir(path) if os.path.isdir(os.path.join(path,d))]`	—	`[p for p in Path(path).iterdir() if p.is_dir()]`
Match pattern in current dir	—	`glob.glob("*.txt")`	`Path(path).glob("*.txt")`
Match pattern with subfolders	—	`glob.glob("*/.txt", recursive=True)`	`Path(path).rglob("*.txt")`
Match by prefix	`[f for f in os.listdir(path) if f.startswith("run_")]`	—	`[p for p in Path(path).iterdir() if p.name.startswith("run_")]`
Match by suffix	`[f for f in os.listdir(path) if f.endswith(".txt")]`	`glob.glob("*.txt")`	`Path(path).glob("*.txt")`
Full path for matches	`[os.path.join(path,f) for f in os.listdir(path)]`	`[os.path.abspath(p) for p in glob.glob("*.txt")]`	`list(Path(path).glob("*.txt"))` (already full path)
Sorted results	`sorted(os.listdir(path))`	`sorted(glob.glob("*.txt"))`	`sorted(Path(path).glob("*.txt"))`
Multiple patterns	—	`chain.from_iterable(glob.glob(p) for p in [".tcl",".py"])`	`list(chain.from_iterable(Path(path).glob(p) for p in [".tcl",".py"]))`
Natural sort	(custom key with `re`)	(same custom key)	(same custom key)

Tips for Choosing a Method#

os.listdir() — fastest for raw directory listings, but no pattern matching. Use with filtering logic.
glob.glob() — simplest for wildcards (*, ?, [abc]), supports recursive search.
pathlib.Path.glob() / .rglob() — modern, chainable, works well with other path operations (.name, .stem, .suffix).

Example: Cross-Platform Replacement for#

os.system(f'ls {dataDir}/*Lcol{Lcol}.out')

import glob, os

pattern = os.path.join(dataDir, f"*Lcol{Lcol}.out")
files = sorted(glob.glob(pattern))
for f in files:
    print(f)

Pathlib version:

from pathlib import Path

files = sorted(Path(dataDir).glob(f"*Lcol{Lcol}.out"))
for p in files:
    print(p)

Directory Contents

Contents

Directory Contents#

os.listdir(): Simple Directory Listing#

Wildcards the Right Way: glob and pathlib#

glob.glob()#

pathlib.Path.glob()#

Why not os.system(‘ls …’)?#

Why use glob instead of os.system(‘ls …’)?#

Quick Comparison#

Drop‑in Replacement for ls {dataDir}/*Lcol{Lcol}.out#

Best Practices & Gotchas#

Splitting into files and directories#

Why this is helpful#

Recipe Box: Common File Listing Patterns#

1. List Only Files (no directories)#

2. List Only Directories#

3. Match by Suffix / Extension#

4. Match by Prefix#

5. Recursive Search (all subfolders)#

6. Natural Sort (sort by embedded numbers, like file2, file10)#

7. Combine Multiple Patterns#

8. Ignore Certain Files#

9. Get Full Paths for All Matches#

10. Mixed Example: List .out files containing Lcol12, sorted#

Python Paths & Wildcards — Quick Reference Cheat Sheet#

Tips for Choosing a Method#

Example: Cross-Platform Replacement for#

Drop‑in Replacement for `ls {dataDir}/*Lcol{Lcol}.out`#

6. Natural Sort (sort by embedded numbers, like `file2`, `file10`)#

10. Mixed Example: List `.out` files containing `Lcol12`, sorted#